Label-free plasmonic spectral profiling of serum DNA

Area of Science:

• Biomedical Engineering
• Molecular Biology
• Nanotechnology

Background:

• Genetic and epigenetic alterations drive cancer development by affecting oncogenes and tumor suppressor genes.
• Accurate molecular profiling is essential for precision medicine and personalized cancer therapy.
• Current DNA analysis methods are complex, time-consuming, and risk sample degradation.

Purpose of the Study:

• To develop a non-invasive, direct, and efficient method for molecular profiling of serum DNA.
• To enable sensitive and specific detection of epigenetic and genetic changes at the single-nucleotide level.
• To present a versatile platform for analyzing biological markers in their native form.

Main Methods:

• Utilized surface-enhanced Raman spectroscopy (SERS) combined with machine learning.
• Developed a plasmonic nanostructured platform for enhanced signal detection.
• Applied the strategy to detect DNA methylation (epigenetic) and single-point mutations (genetic) in serum DNA.

Main Results:

• Achieved sensitive and specific label-free detection of DNA methylation and single-point mutations in serum.
• Demonstrated the capability to analyze genetic and epigenetic changes at the single-nucleotide level.
• Validated the potential of the platform for analyzing DNA in its pristine form.

Conclusions:

• The presented strategy offers a promising approach for direct, efficient, and label-free molecular profiling of serum DNA.
• This method can aid in early cancer diagnosis and the development of personalized therapeutics.
• The versatile platform has broad applications for analyzing various biological markers.